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Certain new ascendant data center workloads can absorb some degradation innetwork service, not needing fully reliable data transport and/or theirfair-share of network bandwidth. This opens up opportunities for superiornetwork and infrastructure multiplexing by having this flexible traffic cedecapacity under congestion to regular traffic with stricter needs. We positthere is opportunity in network service primitives which permit degradationwithin certain bounds, such that flexible traffic still receives an acceptablelevel of service, while benefiting from its weaker requirements. We propose twoprimitives, namely guaranteed partial delivery and bounded deprioritization. Wedesign a budgeting algorithm to provide guarantees relative to their fairshare, which is measured via probing. The requirement of budgeting and probinglimits the algorithm's applicability to large flexible flows.  We evaluate our algorithm with large flexible flows and for three workloadsof regular flows of small size, large size and a distribution of sizes. Acrossthe workloads, our algorithm achieves less speed-up of regular flows than fixedprioritization, especially for the small flows workload (1.25x vs. 6.82 in the99th %-tile). Our algorithm provides better guarantees in the workload withlarge regular flows (with 14.5% vs. 32.5% of flexible flows being slowed downbeyond their guarantee). However, it provides not much better or even slightlyworse guarantees for the other two workloads. The ability to enforce guaranteesis influenced by flow fair share interdependence, measurement inaccuracies anddependency on convergence. We observe that priority changes to probe or todeprioritize causes queue shifts which deteriorate guarantees and limitpossible speed-up, especially of small flows. We find that mechanisms to bothprioritize traffic and track guarantees should be as non-disruptive aspossible.

New primitives for bounded degradation in network service